TY - THES A1 - Michel, René T1 - Simulation and Estimation in Multivariate Generalized Pareto Models T1 - Simulationen und Schätzverfahren in multivariaten verallgemeinerten Pareto-Modellen N2 - The investigation of multivariate generalized Pareto distributions (GPDs) in the framework of extreme value theory has begun only lately. Recent results show that they can, as in the univariate case, be used in Peaks over Threshold approaches. In this manuscript we investigate the definition of GPDs from Section 5.1 of Falk et al. (2004), which does not differ in the area of interest from those of other authors. We first show some theoretical properties and introduce important examples of GPDs. For the further investigation of these distributions simulation methods are an important part. We describe several methods of simulating GPDs, beginning with an efficient method for the logistic GPD. This algorithm is based on the Shi transformation, which was introduced by Shi (1995) and was used in Stephenson (2003) for the simulation of multivariate extreme value distributions of logistic type. We also present nonparametric and parametric estimation methods in GPD models. We estimate the angular density nonparametrically in arbitrary dimension, where the bivariate case turns out to be a special case. The asymptotic normality of the corresponding estimators is shown. Also in the parametric estimations, which are mainly based on maximum likelihood methods, the asymptotic normality of the estimators is shown under certain regularity conditions. Finally the methods are applied to a real hydrological data set containing water discharges of the rivers Altmühl and Danube in southern Bavaria. N2 - Die Untersuchung der multivariaten verallgemeinerten Pareto-Verteilungen (GPDs) im Rahmen der Extremwerttheorie hat erst kürzlich begonnen. Neueste Ergebnisse zeigen, dass diese wie im univariaten Fall bei Peaks over Threshold-Ansätzen angewendet werden können. In dieser Arbeit verwenden wir die Definition einer GPD aus Abschnitt 5.1 von Falk et al. (2004), die sich im interessierenden Bereich nicht von der anderer Autoren unterscheidet. Wir zeigen zuerst einige theoretische Eigenschaften und stellen wichtige Beispiele von GPDs vor. Zur weiteren Untersuchung dieser Verteilungen sind Simulationen unerläßlich. Wir stellen mehrere Methoden zur Simulation von GPDs vor, beginnend mit einer effizienten Methode für die logistische GPD. Der entsprechende Algorithmus basiert auf der Shi-Transformation, die von Shi (1995) eingeführt und von Stephenson (2003) verwendet wurde, um logistische multivariate Extremwertverteilungen zu simulieren. Wir führen auch nicht-parametrische und parametrische Schätzverfahren in GPD-Modellen ein. Wir schätzen die Angular Density in beliebiger Dimension, wobei sich der bivariate Fall als ein besonderer herausstellt. Die asymptotische Normalität der entsprechenden Schätzer wird gezeigt. Ebenso zeigen wir für die parametrischen Schätzungen, die hauptsächlich Maximum-Likelihood-Methoden verwenden, die asymptotische Normalität unter geeigneten Regularitätsbedingungen Zum Schluß werden die Methoden auf einen realen hydrologischen Datensatz, bestehend aus Abflussraten der Flüsse Altmühl und Donau in Südbayern, angewendet. KW - Pareto-Verteilung KW - Multivariate verallgemeine Pareto-Verteilungen KW - Extremwerttheorie KW - Überschreitungen KW - Simulation KW - Angular Density KW - Multivariate Generalized Pareto Distributions KW - Peaks over Threshold KW - Extreme Value Theory KW - Simulation KW - Angular Density Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-18489 ER - TY - BOOK A1 - Falk, Michael A1 - Marohn, Frank A1 - Michel, René A1 - Hofmann, Daniel A1 - Macke, Maria A1 - Tewes, Bernward A1 - Dinges, Peter A1 - Spachmann, Christoph A1 - Englert, Stefan T1 - A First Course on Time Series Analysis : Examples with SAS N2 - The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first three chapters can be dealt within the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 4, 5 and 6 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. Chapter 7 (case study) deals with a practical case and demonstrates the presented methods. It is possible to use this chapter independent in a seminar or practical training course, if the concepts of time series analysis are already well understood. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific parts are highlighted. This book is an open source project under the GNU Free Documentation License. KW - Zeitreihenanalyse KW - Box-Jenkins-Verfahren KW - SAS KW - Zustandsraummodelle KW - Time Series Analysis KW - State-Space Models KW - Frequency Domain KW - Box–Jenkins Program Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-56489 N1 - Version: 2011-March-01 ER - TY - BOOK A1 - Falk, Michael A1 - Marohn, Frank A1 - Michel, René A1 - Hofmann, Daniel A1 - Macke, Maria A1 - Tewes, Bernward A1 - Dinges, Peter T1 - A First Course on Time Series Analysis : Examples with SAS N2 - The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS Statistical Analysis System). Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first two chapters can be dealt with in the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 3, 4 and 5 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific part, including the diagrams generated with SAS, always starts with a computer symbol, representing the beginning of a session at the computer, and ends with a printer symbol for the end of this session. This book is an open source project under the GNU Free Documentation License. KW - Zeitreihenanalyse KW - SAS KW - Zeitreihenanalyse KW - SAS KW - Time series analyses KW - SAS Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-12593 ER - TY - BOOK A1 - Falk, Michael A1 - Marohn, Frank A1 - Michel, René A1 - Hofmann, Daniel A1 - Macke, Maria A1 - Tewes, Bernward A1 - Dinges, Peter T1 - A First Course on Time Series Analysis : Examples with SAS N2 - The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS Statistical Analysis System). Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first two chapters can be dealt with in the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 3, 4 and 5 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific part, including the diagrams generated with SAS, always starts with a computer symbol, representing the beginning of a session at the computer, and ends with a printer symbol for the end of this session. This book is an open source project under the GNU Free Documentation License. KW - Zeitreihenanalyse KW - SAS KW - Zeitreihenanalyse KW - SAS KW - Time series analyses KW - SAS Y1 - 2006 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-16919 ER - TY - BOOK A1 - Falk, Michael A1 - Marohn, Frank A1 - Michel, René A1 - Hofmann, Daniel A1 - Macke, Maria A1 - Spachmann, Christoph A1 - Englert, Stefan T1 - A First Course on Time Series Analysis : Examples with SAS [Version 2012.August.01] N2 - The analysis of real data by means of statistical methods with the aid of a software package common in industry and administration usually is not an integral part of mathematics studies, but it will certainly be part of a future professional work. The present book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. Consequently this book addresses students of statistics as well as students of other branches such as economics, demography and engineering, where lectures on statistics belong to their academic training. But it is also intended for the practician who, beyond the use of statistical tools, is interested in their mathematical background. Numerous problems illustrate the applicability of the presented statistical procedures, where SAS gives the solutions. The programs used are explicitly listed and explained. No previous experience is expected neither in SAS nor in a special computer system so that a short training period is guaranteed. This book is meant for a two semester course (lecture, seminar or practical training) where the first three chapters can be dealt within the first semester. They provide the principal components of the analysis of a time series in the time domain. Chapters 4, 5 and 6 deal with its analysis in the frequency domain and can be worked through in the second term. In order to understand the mathematical background some terms are useful such as convergence in distribution, stochastic convergence, maximum likelihood estimator as well as a basic knowledge of the test theory, so that work on the book can start after an introductory lecture on stochastics. Each chapter includes exercises. An exhaustive treatment is recommended. Chapter 7 (case study) deals with a practical case and demonstrates the presented methods. It is possible to use this chapter independent in a seminar or practical training course, if the concepts of time series analysis are already well understood. This book is consecutively subdivided in a statistical part and an SAS-specific part. For better clearness the SAS-specific parts are highlighted. This book is an open source project under the GNU Free Documentation License. KW - Zeitreihenanalyse KW - Box-Jenkins-Verfahren KW - SAS KW - Zustandsraummodelle KW - Time Series Analysis KW - State-Space Models KW - Frequency Domain KW - Box–Jenkins Program Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-72617 N1 - Version: 2012-August-01 ER - TY - JOUR A1 - Bousquet, Jean A1 - Anto, Josep M. A1 - Bachert, Claus A1 - Haahtela, Tari A1 - Zuberbier, Torsten A1 - Czarlewski, Wienczyslawa A1 - Bedbrook, Anna A1 - Bosnic‐Anticevich, Sinthia A1 - Walter Canonica, G. A1 - Cardona, Victoria A1 - Costa, Elisio A1 - Cruz, Alvaro A. A1 - Erhola, Marina A1 - Fokkens, Wytske J. A1 - Fonseca, Joao A. A1 - Illario, Maddalena A1 - Ivancevich, Juan‐Carlos A1 - Jutel, Marek A1 - Klimek, Ludger A1 - Kuna, Piotr A1 - Kvedariene, Violeta A1 - Le, LTT A1 - Larenas‐Linnemann, Désirée E. A1 - Laune, Daniel A1 - Lourenço, Olga M. A1 - Melén, Erik A1 - Mullol, Joaquim A1 - Niedoszytko, Marek A1 - Odemyr, Mikaëla A1 - Okamoto, Yoshitaka A1 - Papadopoulos, Nikos G. A1 - Patella, Vincenzo A1 - Pfaar, Oliver A1 - Pham‐Thi, Nhân A1 - Rolland, Christine A1 - Samolinski, Boleslaw A1 - Sheikh, Aziz A1 - Sofiev, Mikhail A1 - Suppli Ulrik, Charlotte A1 - Todo‐Bom, Ana A1 - Tomazic, Peter‐Valentin A1 - Toppila‐Salmi, Sanna A1 - Tsiligianni, Ioanna A1 - Valiulis, Arunas A1 - Valovirta, Erkka A1 - Ventura, Maria‐Teresa A1 - Walker, Samantha A1 - Williams, Sian A1 - Yorgancioglu, Arzu A1 - Agache, Ioana A1 - Akdis, Cezmi A. A1 - Almeida, Rute A1 - Ansotegui, Ignacio J. A1 - Annesi‐Maesano, Isabella A1 - Arnavielhe, Sylvie A1 - Basagaña, Xavier A1 - D. Bateman, Eric A1 - Bédard, Annabelle A1 - Bedolla‐Barajas, Martin A1 - Becker, Sven A1 - Bennoor, Kazi S. A1 - Benveniste, Samuel A1 - Bergmann, Karl C. A1 - Bewick, Michael A1 - Bialek, Slawomir A1 - E. Billo, Nils A1 - Bindslev‐Jensen, Carsten A1 - Bjermer, Leif A1 - Blain, Hubert A1 - Bonini, Matteo A1 - Bonniaud, Philippe A1 - Bosse, Isabelle A1 - Bouchard, Jacques A1 - Boulet, Louis‐Philippe A1 - Bourret, Rodolphe A1 - Boussery, Koen A1 - Braido, Fluvio A1 - Briedis, Vitalis A1 - Briggs, Andrew A1 - Brightling, Christopher E. A1 - Brozek, Jan A1 - Brusselle, Guy A1 - Brussino, Luisa A1 - Buhl, Roland A1 - Buonaiuto, Roland A1 - Calderon, Moises A. A1 - Camargos, Paulo A1 - Camuzat, Thierry A1 - Caraballo, Luis A1 - Carriazo, Ana‐Maria A1 - Carr, Warner A1 - Cartier, Christine A1 - Casale, Thomas A1 - Cecchi, Lorenzo A1 - Cepeda Sarabia, Alfonso M. A1 - H. Chavannes, Niels A1 - Chkhartishvili, Ekaterine A1 - Chu, Derek K. A1 - Cingi, Cemal A1 - Correia de Sousa, Jaime A1 - Costa, David J. A1 - Courbis, Anne‐Lise A1 - Custovic, Adnan A1 - Cvetkosvki, Biljana A1 - D'Amato, Gennaro A1 - da Silva, Jane A1 - Dantas, Carina A1 - Dokic, Dejan A1 - Dauvilliers, Yves A1 - De Feo, Giulia A1 - De Vries, Govert A1 - Devillier, Philippe A1 - Di Capua, Stefania A1 - Dray, Gerard A1 - Dubakiene, Ruta A1 - Durham, Stephen R. A1 - Dykewicz, Mark A1 - Ebisawa, Motohiro A1 - Gaga, Mina A1 - El‐Gamal, Yehia A1 - Heffler, Enrico A1 - Emuzyte, Regina A1 - Farrell, John A1 - Fauquert, Jean‐Luc A1 - Fiocchi, Alessandro A1 - Fink‐Wagner, Antje A1 - Fontaine, Jean‐François A1 - Fuentes Perez, José M. A1 - Gemicioğlu, Bilun A1 - Gamkrelidze, Amiran A1 - Garcia‐Aymerich, Judith A1 - Gevaert, Philippe A1 - Gomez, René Maximiliano A1 - González Diaz, Sandra A1 - Gotua, Maia A1 - Guldemond, Nick A. A1 - Guzmán, Maria‐Antonieta A1 - Hajjam, Jawad A1 - Huerta Villalobos, Yunuen R. A1 - Humbert, Marc A1 - Iaccarino, Guido A1 - Ierodiakonou, Despo A1 - Iinuma, Tomohisa A1 - Jassem, Ewa A1 - Joos, Guy A1 - Jung, Ki‐Suck A1 - Kaidashev, Igor A1 - Kalayci, Omer A1 - Kardas, Przemyslaw A1 - Keil, Thomas A1 - Khaitov, Musa A1 - Khaltaev, Nikolai A1 - Kleine‐Tebbe, Jorg A1 - Kouznetsov, Rostislav A1 - Kowalski, Marek L. A1 - Kritikos, Vicky A1 - Kull, Inger A1 - La Grutta, Stefania A1 - Leonardini, Lisa A1 - Ljungberg, Henrik A1 - Lieberman, Philip A1 - Lipworth, Brian A1 - Lodrup Carlsen, Karin C. A1 - Lopes‐Pereira, Catarina A1 - Loureiro, Claudia C. A1 - Louis, Renaud A1 - Mair, Alpana A1 - Mahboub, Bassam A1 - Makris, Michaël A1 - Malva, Joao A1 - Manning, Patrick A1 - Marshall, Gailen D. A1 - Masjedi, Mohamed R. A1 - Maspero, Jorge F. A1 - Carreiro‐Martins, Pedro A1 - Makela, Mika A1 - Mathieu‐Dupas, Eve A1 - Maurer, Marcus A1 - De Manuel Keenoy, Esteban A1 - Melo‐Gomes, Elisabete A1 - Meltzer, Eli O. A1 - Menditto, Enrica A1 - Mercier, Jacques A1 - Micheli, Yann A1 - Miculinic, Neven A1 - Mihaltan, Florin A1 - Milenkovic, Branislava A1 - Mitsias, Dimitirios I. A1 - Moda, Giuliana A1 - Mogica‐Martinez, Maria‐Dolores A1 - Mohammad, Yousser A1 - Montefort, Steve A1 - Monti, Ricardo A1 - Morais‐Almeida, Mario A1 - Mösges, Ralph A1 - Münter, Lars A1 - Muraro, Antonella A1 - Murray, Ruth A1 - Naclerio, Robert A1 - Napoli, Luigi A1 - Namazova‐Baranova, Leyla A1 - Neffen, Hugo A1 - Nekam, Kristoff A1 - Neou, Angelo A1 - Nordlund, Björn A1 - Novellino, Ettore A1 - Nyembue, Dieudonné A1 - O'Hehir, Robyn A1 - Ohta, Ken A1 - Okubo, Kimi A1 - Onorato, Gabrielle L. A1 - Orlando, Valentina A1 - Ouedraogo, Solange A1 - Palamarchuk, Julia A1 - Pali‐Schöll, Isabella A1 - Panzner, Peter A1 - Park, Hae‐Sim A1 - Passalacqua, Gianni A1 - Pépin, Jean‐Louis A1 - Paulino, Ema A1 - Pawankar, Ruby A1 - Phillips, Jim A1 - Picard, Robert A1 - Pinnock, Hilary A1 - Plavec, Davor A1 - Popov, Todor A. A1 - Portejoie, Fabienne A1 - Price, David A1 - Prokopakis, Emmanuel P. A1 - Psarros, Fotis A1 - Pugin, Benoit A1 - Puggioni, Francesca A1 - Quinones‐Delgado, Pablo A1 - Raciborski, Filip A1 - Rajabian‐Söderlund, Rojin A1 - Regateiro, Frederico S. A1 - Reitsma, Sietze A1 - Rivero‐Yeverino, Daniela A1 - Roberts, Graham A1 - Roche, Nicolas A1 - Rodriguez‐Zagal, Erendira A1 - Rolland, Christine A1 - Roller‐Wirnsberger, Regina E. A1 - Rosario, Nelson A1 - Romano, Antonino A1 - Rottem, Menachem A1 - Ryan, Dermot A1 - Salimäki, Johanna A1 - Sanchez‐Borges, Mario M. A1 - Sastre, Joaquin A1 - Scadding, Glenis K. A1 - Scheire, Sophie A1 - Schmid‐Grendelmeier, Peter A1 - Schünemann, Holger J. A1 - Sarquis Serpa, Faradiba A1 - Shamji, Mohamed A1 - Sisul, Juan‐Carlos A1 - Sofiev, Mikhail A1 - Solé, Dirceu A1 - Somekh, David A1 - Sooronbaev, Talant A1 - Sova, Milan A1 - Spertini, François A1 - Spranger, Otto A1 - Stellato, Cristiana A1 - Stelmach, Rafael A1 - Thibaudon, Michel A1 - To, Teresa A1 - Toumi, Mondher A1 - Usmani, Omar A1 - Valero, Antonio A. A1 - Valenta, Rudolph A1 - Valentin‐Rostan, Marylin A1 - Pereira, Marilyn Urrutia A1 - van der Kleij, Rianne A1 - Van Eerd, Michiel A1 - Vandenplas, Olivier A1 - Vasankari, Tuula A1 - Vaz Carneiro, Antonio A1 - Vezzani, Giorgio A1 - Viart, Frédéric A1 - Viegi, Giovanni A1 - Wallace, Dana A1 - Wagenmann, Martin A1 - Wang, De Yun A1 - Waserman, Susan A1 - Wickman, Magnus A1 - Williams, Dennis M. A1 - Wong, Gary A1 - Wroczynski, Piotr A1 - Yiallouros, Panayiotis K. A1 - Yusuf, Osman M. A1 - Zar, Heather J. A1 - Zeng, Stéphane A1 - Zernotti, Mario E. A1 - Zhang, Luo A1 - Shan Zhong, Nan A1 - Zidarn, Mihaela T1 - ARIA digital anamorphosis: Digital transformation of health and care in airway diseases from research to practice JF - Allergy N2 - Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed. KW - ARIA KW - asthma KW - CARAT KW - digital transformation of health and care KW - MASK KW - rhinitis Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-228339 VL - 76 IS - 1 SP - 168 EP - 190 ER -